Integration to Grav for Customer Empowerment
Grav is a modern open source flat-file CMS able to create a powerful digital user experience when making a website. Raffle will be able to empower the users' navigation on the platform
Performance
Zero-shot ("out of the box") percentage correct answers in top 3.
Accuracy
80%
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Zero-shot ("out of the box") percentage correct answers in top 3.
Accuracy improves over time
Train models on user feedback signals.
Answer latency
< 1 Second
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Raffle uses advanced deep learning models that increase the time it takes to answer. Traditional information retrieval is fast.
Mean reciprocal rank (MRR)
0.65-0.99
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Mean reciprocal rank of clicked answer (expert metric).
Resolution rate (RR)
0.4-0.9
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Fraction of searches where user clicked on a search result.
File formats
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File formats supported.
Search
Zero-shot ("out of the box") percentage correct answers in top 3.
Keyword search
Search using keywords.
Semantic search
Designed to search with natural language sentences.
Insights
Zero-shot ("out of the box") percentage correct answers in top 3.
Trending questions
What are the users mainly asking about right now.
Knowledge gaps
What are the users asking about right now that they don't get answered because it is not in knowledge source.
Instant answers
Possibility for adding a frequently asked question knowledge source for example to address knowledge gaps and trending questions.
Other
Zero-shot ("out of the box") percentage correct answers in top 3.
GPDR tools
Tools to remove and identify personal user information from knowledge sources and user input.
Documents in knowledge source
10^5(*) - 10^8(**)
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(*) Raffle's deep learning solution is memory intensive but accurate. (**) Traditional information retrieval is available for large knowledge sources.
